On Optimal Designs For Linear MIMO Transceivers

It is all about spectrum. Wireless industry is experiencing its fastest growing since Marconi pioneered the wireless technology one hundred years ago, which is due to the research and application of advanced communications technology. The gradual evolution of mobile communication system follows the quest for high data rates, and the demands on bandwidth and spectral availability seem to be endless. So, wireless designers have to face an uphill task of limited availability of radio frequency spectrum problem in the wireless channel. Multiple-input multiple-output (MIMO) technology has attracted a large amount of attention in wireless communications, because it offers a promising solution to support greater data rate and higher reliability over wireless links without additional bandwidth or transmit power. As a result, MIMO systems have been a current theme of international wireless research.To achieve better performance, precoding and decoding design becomes an im-portant challenge in the future wireless MIMO communication systems. The main objective of this thesis is to provide a series of optimal designs for MIMO transceivers including:optimal design for linear MIMO transceivers by using directional derivative, optimal power allocation via Majorization theory with quality of service (QoS) con-straints, and optimal user selection and QoS control for multi-users MIMO systems. Directional derivative and Majorization theory are the underlying mathematical theo-ries on which our methods hinge. The concrete contributions and innovations of the thesis are listed as follows:Optimal design for minimizing the combination of symbol estimation errors sub-ject to lp-norm constraint is investigated. Instead of considering each constraint in a separate way, we develop a unifying framework to obtain the optimal solution by employing a directional derivative method. Moreover, based on directional derivative, we show that the minimization of the determinant of mean-square er-ror matrix and the maximization of mutual information are equivalent criteria.A unified framework is developed to obtain the optimal precoder designs for several different criteria with the realistic power constraints jointly imposed on both the sum power and the peak power. It is shown that power allocation is piecewise linear in the sum power, and thus finding the entire path of solution for every value of the sum power just requires checking a finite number of points. Our method is computationally efficient and outperforms existing methods in the literature which can only give approximate solutions.Optimal power allocation for maximizing the sum capacity of the reverse link of multi-rate CDMA systems with QoS constraints is investigated. It is shown that the structure of the optimal solution can be easily obtained via Majorization theory. Furthermore, based on our new approach, an efficient searching method for power allocation is developed. Our new method requires only approximately a half of the computational cost of existing methods in the worst case and is even much faster in general.Max-min fair power allocation brings higher average throughput and better uti-lization of the resources than a work-conserving equal sharing policy. Instead of achieving a common maximum sum-rate objective, an optimal power allo-cation design for maximizing the minimum rate of the reverse-link of CDMA systems with QoS constraints is investigated. We first try to derive the structure of the optimal solution via Majorization theory. Then, we propose a very effi-cient search method to find the max-min fair solution. Compared with existing methods, much lighter computational complexity is required by our method.An efficient greedy scheduler for zero-forcing dirty-paper coding (ZF-DPC), which can be incorporated in complex Householder QR factorization of the channel ma-trix, is proposed. The ratio of the complexity of the proposed scheduler to the complexity of the channel matrix factorization required by ZF-DPC is O(M-1), while such ratio for the original greedy scheduler is O(M), where M is the number of transmitters. Therefore, the new scheduler reduces the overhead of scheduling from being the bottleneck of ZF-DPC to being negligible.In an attempt to admit new users into CDMA communication systems in the case of overload, an optimal proportional QoS reduction method subject to a weighted sum power constraint is investigated. Based on the Perron-Frobenius Theorem, we successfully derive an optimal closed-form solution. Compared to existing methods, our method greatly reduces the computational complexity, as well as maintains high reliability.